package cn.iocoder.yudao.module.crossborder.platform.service.provider.amazon;

import cn.iocoder.yudao.module.crossborder.platform.dal.dataobject.platformauth.PlatformAuthDO;
import cn.iocoder.yudao.module.crossborder.platform.dal.dataobject.platformstore.PlatformStoreDO;
import cn.iocoder.yudao.module.crossborder.platform.dal.dataobject.platformsynctask.PlatformSyncTaskDO;
import cn.iocoder.yudao.module.crossborder.platform.service.platformauth.PlatformAuthService;
import cn.iocoder.yudao.module.crossborder.platform.service.platformstore.PlatformStoreService;
import cn.iocoder.yudao.module.crossborder.platform.service.platformsynctask.PlatformSyncTaskService;
import cn.iocoder.yudao.module.crossborder.platform.service.provider.amazon.client.AmazonApiClient;
import cn.iocoder.yudao.module.crossborder.platform.service.provider.amazon.client.AmazonMockDataGenerator;
import cn.iocoder.yudao.module.crossborder.platform.service.provider.amazon.config.AmazonPlatformConfig;
import cn.iocoder.yudao.framework.tenant.core.util.TenantUtils;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.scheduling.annotation.Async;
import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.stereotype.Service;

import javax.annotation.Resource;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
import java.util.*;
import java.util.concurrent.CompletableFuture;
import java.util.stream.Collectors;

/**
 * Amazon业务服务
 * 整合Amazon各个Provider，提供统一的业务接口
 *
 * @author 芋道源码
 */
@Service
@Slf4j
public class AmazonBusinessService {

    @Resource
    private AmazonPlatformProvider amazonPlatformProvider;

    @Resource
    private AmazonAuthProvider amazonAuthProvider;

    @Resource
    private AmazonSyncProvider amazonSyncProvider;

    @Resource
    private AmazonWebhookProvider amazonWebhookProvider;

    @Resource
    private AmazonPlatformConfig amazonPlatformConfig;

    @Resource
    private PlatformStoreService platformStoreService;

    @Resource
    private PlatformAuthService platformAuthService;

    @Resource
    private PlatformSyncTaskService platformSyncTaskService;

    @Resource
    private AmazonApiClient amazonApiClient;

    @Resource
    private AmazonMockDataGenerator mockDataGenerator;

    @Value("${amazon.api.mock.enabled:false}")
    private boolean mockEnabled;

    private final DateTimeFormatter dateFormatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");

    /**
     * 设置Amazon店铺
     *
     * @param storeId 店铺ID
     * @param config 店铺配置
     * @return 设置结果
     */
    public Map<String, Object> setupAmazonStore(Long storeId, Map<String, Object> config) {
        log.info("设置Amazon店铺: storeId={}, config={}", storeId, config);
        
        Map<String, Object> result = new HashMap<>();
        
        try {
            // 1. 验证平台配置
            if (!amazonPlatformProvider.validateConfig(config)) {
                result.put("success", false);
                result.put("message", "平台配置验证失败");
                return result;
            }
            
            // 2. 初始化平台
            amazonPlatformProvider.initializePlatform(config);
            
            // 3. 设置授权
            String authUrl = amazonAuthProvider.getAuthUrl(storeId, (String) config.get("redirectUri"));
            
            result.put("success", true);
            result.put("authUrl", authUrl);
            result.put("message", "Amazon店铺设置成功，请完成授权");
            
        } catch (Exception e) {
            log.error("设置Amazon店铺失败", e);
            result.put("success", false);
            result.put("message", "设置失败: " + e.getMessage());
        }
        
        return result;
    }

    /**
     * 执行Amazon数据同步
     *
     * @param storeId 店铺ID
     * @param syncType 同步类型
     * @param startTime 开始时间
     * @param endTime 结束时间
     * @return 同步结果
     */
    public Map<String, Object> executeSync(Long storeId, String syncType, LocalDateTime startTime, LocalDateTime endTime) {
        log.info("执行Amazon数据同步: storeId={}, syncType={}, startTime={}, endTime={}", 
                storeId, syncType, startTime, endTime);
        
        // 1. 验证授权状态
        if (!amazonAuthProvider.validateAuth(storeId)) {
            Map<String, Object> errorResult = new HashMap<>();
            errorResult.put("success", false);
            errorResult.put("message", "店铺授权无效，请重新授权");
            return errorResult;
        }
        
        // 2. 根据同步类型执行同步
        switch (syncType.toUpperCase()) {
            case "ORDERS":
                return amazonSyncProvider.syncOrders(storeId, startTime, endTime);
            case "PRODUCTS":
                return amazonSyncProvider.syncProducts(storeId, startTime, endTime);
            case "INVENTORY":
                return amazonSyncProvider.syncInventory(storeId);
            default:
                Map<String, Object> errorResult = new HashMap<>();
                errorResult.put("success", false);
                errorResult.put("message", "不支持的同步类型: " + syncType);
                return errorResult;
        }
    }

    /**
     * 获取Amazon店铺概览
     *
     * @param storeId 店铺ID
     * @return 店铺概览信息
     */
    public Map<String, Object> getStoreOverview(Long storeId) {
        log.info("获取Amazon店铺概览: storeId={}", storeId);

        Map<String, Object> overview = new HashMap<>();

        try {
            // 1. 获取店铺基本信息
            PlatformStoreDO store = platformStoreService.getPlatformStore(storeId);
            if (store == null) {
                overview.put("error", "店铺不存在");
                return overview;
            }

            // 2. 获取授权状态
            PlatformAuthDO auth = platformAuthService.getPlatformAuthByStoreId(storeId);
            boolean isAuthorized = amazonAuthProvider.validateAuth(storeId);

            // 3. 获取平台健康状态
            boolean isHealthy = amazonPlatformProvider.isHealthy();

            // 4. 构建概览信息
            overview.put("storeId", storeId);
            overview.put("storeName", store.getName());
            overview.put("platform", "Amazon");
            overview.put("region", store.getRegion());
            overview.put("marketplaceId", store.getMarketplaceId());
            overview.put("authStatus", isAuthorized ? "AUTHORIZED" : "UNAUTHORIZED");
            overview.put("healthStatus", isHealthy ? "HEALTHY" : "UNHEALTHY");
            overview.put("storeStatus", store.getStatus());

            if (auth != null) {
                overview.put("authTime", auth.getAuthTime());
                overview.put("lastRefreshTime", auth.getLastRefreshTime());
                overview.put("tokenExpireTime", auth.getTokenExpireTime());
            }

            // 5. 获取同步状态和业务数据统计
            Map<String, Object> syncStats = getSyncStatistics(storeId);
            overview.put("syncStats", syncStats);

            // 6. 获取最近的同步任务
            List<Map<String, Object>> recentTasks = getRecentSyncTasks(storeId, 5);
            overview.put("recentTasks", recentTasks);

        } catch (Exception e) {
            log.error("获取Amazon店铺概览失败: storeId={}", storeId, e);
            overview.put("error", e.getMessage());
        }

        return overview;
    }

    /**
     * 获取Amazon店铺数据分析
     *
     * @param storeId 店铺ID
     * @param days 分析天数
     * @return 数据分析结果
     */
    public Map<String, Object> getStoreAnalytics(Long storeId, Integer days) {
        log.info("获取Amazon店铺数据分析: storeId={}, days={}", storeId, days);

        Map<String, Object> analytics = new HashMap<>();

        try {
            // 1. 验证授权状态
            if (!amazonAuthProvider.validateAuth(storeId)) {
                analytics.put("error", "店铺授权无效");
                return analytics;
            }

            // 2. 获取销售数据分析
            Map<String, Object> salesAnalytics = getSalesAnalytics(storeId, days);
            analytics.put("sales", salesAnalytics);

            // 3. 获取商品数据分析
            Map<String, Object> productAnalytics = getProductAnalytics(storeId, days);
            analytics.put("products", productAnalytics);

            // 4. 获取库存分析
            Map<String, Object> inventoryAnalytics = getInventoryAnalytics(storeId);
            analytics.put("inventory", inventoryAnalytics);

            // 5. 获取订单分析
            Map<String, Object> orderAnalytics = getOrderAnalytics(storeId, days);
            analytics.put("orders", orderAnalytics);

            analytics.put("success", true);
            analytics.put("analysisDate", LocalDateTime.now().format(dateFormatter));
            analytics.put("analysisPeriod", days + " days");

        } catch (Exception e) {
            log.error("获取Amazon店铺数据分析失败: storeId={}", storeId, e);
            analytics.put("error", e.getMessage());
        }

        return analytics;
    }

    /**
     * 获取库存预警信息
     *
     * @param storeId 店铺ID
     * @return 库存预警信息
     */
    public Map<String, Object> getInventoryAlerts(Long storeId) {
        log.info("获取Amazon库存预警: storeId={}", storeId);

        Map<String, Object> alerts = new HashMap<>();

        try {
            // 1. 验证授权状态
            if (!amazonAuthProvider.validateAuth(storeId)) {
                alerts.put("error", "店铺授权无效");
                return alerts;
            }

            // 2. 获取低库存商品
            List<Map<String, Object>> lowStockItems = getLowStockItems(storeId);
            alerts.put("lowStock", lowStockItems);

            // 3. 获取缺货商品
            List<Map<String, Object>> outOfStockItems = getOutOfStockItems(storeId);
            alerts.put("outOfStock", outOfStockItems);

            // 4. 获取滞销商品
            List<Map<String, Object>> slowMovingItems = getSlowMovingItems(storeId);
            alerts.put("slowMoving", slowMovingItems);

            // 5. 统计信息
            alerts.put("totalLowStock", lowStockItems.size());
            alerts.put("totalOutOfStock", outOfStockItems.size());
            alerts.put("totalSlowMoving", slowMovingItems.size());
            alerts.put("alertLevel", calculateAlertLevel(lowStockItems.size(), outOfStockItems.size()));

            alerts.put("success", true);
            alerts.put("checkTime", LocalDateTime.now().format(dateFormatter));

        } catch (Exception e) {
            log.error("获取Amazon库存预警失败: storeId={}", storeId, e);
            alerts.put("error", e.getMessage());
        }

        return alerts;
    }

    /**
     * 批量执行数据同步
     *
     * @param storeId 店铺ID
     * @param syncTypes 同步类型列表
     * @param startTime 开始时间
     * @param endTime 结束时间
     * @return 批量同步结果
     */
    @Async
    public CompletableFuture<Map<String, Object>> batchSync(Long storeId, List<String> syncTypes,
                                                           LocalDateTime startTime, LocalDateTime endTime) {
        log.info("批量执行Amazon数据同步: storeId={}, syncTypes={}", storeId, syncTypes);

        Map<String, Object> result = new HashMap<>();
        Map<String, Object> syncResults = new HashMap<>();

        try {
            // 1. 验证授权状态
            if (!amazonAuthProvider.validateAuth(storeId)) {
                result.put("success", false);
                result.put("message", "店铺授权无效");
                return CompletableFuture.completedFuture(result);
            }

            // 2. 并行执行同步任务
            List<CompletableFuture<Map<String, Object>>> futures = syncTypes.stream()
                .map(syncType -> CompletableFuture.supplyAsync(() ->
                    executeSync(storeId, syncType, startTime, endTime)))
                .collect(Collectors.toList());

            // 3. 等待所有任务完成
            CompletableFuture.allOf(futures.toArray(new CompletableFuture[0])).join();

            // 4. 收集结果
            for (int i = 0; i < syncTypes.size(); i++) {
                String syncType = syncTypes.get(i);
                Map<String, Object> syncResult = futures.get(i).get();
                syncResults.put(syncType, syncResult);
            }

            result.put("success", true);
            result.put("syncResults", syncResults);
            result.put("message", "批量同步完成");

        } catch (Exception e) {
            log.error("批量执行Amazon数据同步失败: storeId={}", storeId, e);
            result.put("success", false);
            result.put("message", "批量同步失败: " + e.getMessage());
        }

        return CompletableFuture.completedFuture(result);
    }

    /**
     * 定时刷新访问令牌
     */
    @Scheduled(fixedRate = 1800000) // 每30分钟执行一次
    public void refreshExpiredTokens() {
        log.debug("开始定时刷新过期的Amazon访问令牌");

        try {
            // 注意：忽略自动多租户，因为要全局刷新令牌
            TenantUtils.executeIgnore(() -> {
                // 获取即将过期的授权列表（提前1小时刷新）
                LocalDateTime expireThreshold = LocalDateTime.now().plusHours(1);
                List<PlatformAuthDO> expiredAuths = platformAuthService.getExpiredAuthList(expireThreshold);

                for (PlatformAuthDO auth : expiredAuths) {
                    if (auth.getAutoRefresh()) {
                        try {
                            boolean refreshed = amazonAuthProvider.refreshAccessToken(auth.getStoreId());
                            if (refreshed) {
                                log.info("自动刷新Amazon访问令牌成功: storeId={}", auth.getStoreId());
                            } else {
                                log.warn("自动刷新Amazon访问令牌失败: storeId={}", auth.getStoreId());
                            }
                        } catch (Exception e) {
                            log.error("自动刷新Amazon访问令牌异常: storeId={}", auth.getStoreId(), e);
                        }
                    }
                }
            });
        } catch (Exception e) {
            log.error("定时刷新Amazon访问令牌失败", e);
        }
    }

    /**
     * 定时健康检查
     */
    @Scheduled(fixedRate = 300000) // 每5分钟执行一次
    public void healthCheck() {
        log.debug("开始Amazon平台健康检查");

        try {
            // 注意：忽略自动多租户，因为要全局健康检查
            TenantUtils.executeIgnore(() -> {
                boolean isHealthy = amazonPlatformProvider.isHealthy();
                if (!isHealthy) {
                    log.warn("Amazon平台健康检查失败");
                    // TODO: 发送告警通知
                }
            });
        } catch (Exception e) {
            log.error("Amazon平台健康检查异常", e);
        }
    }

    // ==================== 辅助方法 ====================

    /**
     * 获取同步统计信息
     */
    private Map<String, Object> getSyncStatistics(Long storeId) {
        Map<String, Object> stats = new HashMap<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据
                int totalTasks = mockDataGenerator.generateQuantity(20, 100);
                int successTasks = (int) (totalTasks * 0.85); // 85%成功率
                int failedTasks = totalTasks - successTasks;

                stats.put("totalTasks", totalTasks);
                stats.put("successTasks", successTasks);
                stats.put("failedTasks", failedTasks);
                stats.put("successRate", String.format("%.1f%%", (double) successTasks / totalTasks * 100));
                stats.put("lastSyncTime", mockDataGenerator.generateDateTime(1));
            } else {
                // TODO: 实现真实的同步统计逻辑
                // 1. 统计最近24小时的同步任务
                // 2. 统计成功/失败的任务数量
                // 3. 计算同步成功率

                stats.put("totalTasks", 0);
                stats.put("successTasks", 0);
                stats.put("failedTasks", 0);
                stats.put("successRate", "0%");
                stats.put("lastSyncTime", null);
            }

        } catch (Exception e) {
            log.error("获取同步统计信息失败: storeId={}", storeId, e);
        }

        return stats;
    }

    /**
     * 获取最近的同步任务
     */
    private List<Map<String, Object>> getRecentSyncTasks(Long storeId, int limit) {
        List<Map<String, Object>> tasks = new ArrayList<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据生成最近的同步任务
                String[] syncTypes = {"ORDERS", "PRODUCTS", "INVENTORY"};
                String[] statuses = {"SUCCESS", "FAILED", "RUNNING"};

                for (int i = 0; i < limit; i++) {
                    Map<String, Object> task = new HashMap<>();
                    task.put("taskId", "TASK-" + (System.currentTimeMillis() + i));
                    task.put("syncType", mockDataGenerator.randomChoice(syncTypes));
                    task.put("status", mockDataGenerator.randomChoice(statuses));
                    task.put("startTime", mockDataGenerator.generateDateTime(7));
                    task.put("endTime", mockDataGenerator.generateDateTime(6));
                    task.put("recordCount", mockDataGenerator.generateQuantity(10, 500));
                    task.put("successCount", mockDataGenerator.generateQuantity(8, 450));
                    task.put("failedCount", mockDataGenerator.generateQuantity(0, 50));
                    tasks.add(task);
                }
            } else {
                // TODO: 实现最近同步任务查询逻辑
                // 1. 查询最近的同步任务
                // 2. 转换为前端需要的格式
            }

        } catch (Exception e) {
            log.error("获取最近同步任务失败: storeId={}", storeId, e);
        }

        return tasks;
    }

    /**
     * 获取销售数据分析
     */
    private Map<String, Object> getSalesAnalytics(Long storeId, Integer days) {
        Map<String, Object> analytics = new HashMap<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据
                double totalSales = mockDataGenerator.generatePrice(10000, 100000).doubleValue();
                int totalOrders = mockDataGenerator.generateQuantity(100, 1000);
                double averageOrderValue = totalSales / totalOrders;
                String[] trends = {"increasing", "decreasing", "stable"};

                analytics.put("totalSales", totalSales);
                analytics.put("totalOrders", totalOrders);
                analytics.put("averageOrderValue", Math.round(averageOrderValue * 100.0) / 100.0);
                analytics.put("salesTrend", mockDataGenerator.randomChoice(trends));

                // 添加每日销售数据
                List<Map<String, Object>> dailySales = new ArrayList<>();
                for (int i = days - 1; i >= 0; i--) {
                    Map<String, Object> daySale = new HashMap<>();
                    daySale.put("date", mockDataGenerator.generateDateTime(i).substring(0, 10));
                    daySale.put("sales", mockDataGenerator.generatePrice(200, 2000).doubleValue());
                    daySale.put("orders", mockDataGenerator.generateQuantity(5, 50));
                    dailySales.add(daySale);
                }
                analytics.put("dailySales", dailySales);
            } else {
                // TODO: 实现销售数据分析逻辑
                // 1. 调用Amazon Reports API获取销售报告
                // 2. 分析销售趋势、热销商品等

                analytics.put("totalSales", 0.0);
                analytics.put("totalOrders", 0);
                analytics.put("averageOrderValue", 0.0);
                analytics.put("salesTrend", "stable");
            }

        } catch (Exception e) {
            log.error("获取销售数据分析失败: storeId={}", storeId, e);
        }

        return analytics;
    }

    /**
     * 获取商品数据分析
     */
    private Map<String, Object> getProductAnalytics(Long storeId, Integer days) {
        Map<String, Object> analytics = new HashMap<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据
                int totalProducts = mockDataGenerator.generateQuantity(50, 500);
                int activeProducts = (int) (totalProducts * 0.9); // 90%活跃

                analytics.put("totalProducts", totalProducts);
                analytics.put("activeProducts", activeProducts);
                analytics.put("averageRating", mockDataGenerator.generateRating().doubleValue());

                // 生成热门分类
                List<Map<String, Object>> topCategories = new ArrayList<>();
                String[] categories = {"Electronics", "Home & Kitchen", "Sports & Outdoors", "Health & Personal Care"};
                for (String category : categories) {
                    Map<String, Object> categoryData = new HashMap<>();
                    categoryData.put("name", category);
                    categoryData.put("count", mockDataGenerator.generateQuantity(10, 100));
                    categoryData.put("percentage", mockDataGenerator.generatePercentage().doubleValue());
                    topCategories.add(categoryData);
                }
                analytics.put("topCategories", topCategories);

                // 生成热销商品
                List<Map<String, Object>> topProducts = new ArrayList<>();
                for (int i = 0; i < 5; i++) {
                    Map<String, Object> product = new HashMap<>();
                    product.put("asin", mockDataGenerator.generateAsin());
                    product.put("title", mockDataGenerator.generateProductName());
                    product.put("sales", mockDataGenerator.generateQuantity(10, 200));
                    product.put("revenue", mockDataGenerator.generatePrice(500, 5000).doubleValue());
                    topProducts.add(product);
                }
                analytics.put("topProducts", topProducts);
            } else {
                // TODO: 实现商品数据分析逻辑
                // 1. 统计商品数量、分类分布
                // 2. 分析商品表现、评分等

                analytics.put("totalProducts", 0);
                analytics.put("activeProducts", 0);
                analytics.put("topCategories", new ArrayList<>());
                analytics.put("averageRating", 0.0);
            }

        } catch (Exception e) {
            log.error("获取商品数据分析失败: storeId={}", storeId, e);
        }

        return analytics;
    }

    /**
     * 获取库存分析
     */
    private Map<String, Object> getInventoryAnalytics(Long storeId) {
        Map<String, Object> analytics = new HashMap<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据
                int totalInventory = mockDataGenerator.generateQuantity(1000, 10000);
                int availableInventory = (int) (totalInventory * 0.85); // 85%可售
                int lowStockCount = mockDataGenerator.generateQuantity(5, 50);
                int outOfStockCount = mockDataGenerator.generateQuantity(0, 20);

                analytics.put("totalInventory", totalInventory);
                analytics.put("availableInventory", availableInventory);
                analytics.put("lowStockCount", lowStockCount);
                analytics.put("outOfStockCount", outOfStockCount);
                analytics.put("reservedInventory", totalInventory - availableInventory);
                analytics.put("inventoryTurnover", mockDataGenerator.generatePercentage().doubleValue());

                // 库存分布
                Map<String, Object> inventoryDistribution = new HashMap<>();
                inventoryDistribution.put("inStock", availableInventory);
                inventoryDistribution.put("lowStock", lowStockCount);
                inventoryDistribution.put("outOfStock", outOfStockCount);
                inventoryDistribution.put("reserved", totalInventory - availableInventory);
                analytics.put("inventoryDistribution", inventoryDistribution);
            } else {
                // TODO: 实现库存分析逻辑
                // 1. 统计总库存、可售库存
                // 2. 分析库存周转率、预警等

                analytics.put("totalInventory", 0);
                analytics.put("availableInventory", 0);
                analytics.put("lowStockCount", 0);
                analytics.put("outOfStockCount", 0);
            }

        } catch (Exception e) {
            log.error("获取库存分析失败: storeId={}", storeId, e);
        }

        return analytics;
    }

    /**
     * 获取订单分析
     */
    private Map<String, Object> getOrderAnalytics(Long storeId, Integer days) {
        Map<String, Object> analytics = new HashMap<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据
                int totalOrders = mockDataGenerator.generateQuantity(100, 1000);
                int pendingOrders = (int) (totalOrders * 0.1); // 10%待处理
                int shippedOrders = (int) (totalOrders * 0.75); // 75%已发货
                int cancelledOrders = (int) (totalOrders * 0.05); // 5%取消
                int deliveredOrders = totalOrders - pendingOrders - shippedOrders - cancelledOrders;

                analytics.put("totalOrders", totalOrders);
                analytics.put("pendingOrders", pendingOrders);
                analytics.put("shippedOrders", shippedOrders);
                analytics.put("deliveredOrders", deliveredOrders);
                analytics.put("cancelledOrders", cancelledOrders);
                analytics.put("returnRate", String.format("%.1f%%", mockDataGenerator.generatePercentage().doubleValue() % 10));

                // 订单状态分布
                Map<String, Object> orderStatusDistribution = new HashMap<>();
                orderStatusDistribution.put("pending", pendingOrders);
                orderStatusDistribution.put("shipped", shippedOrders);
                orderStatusDistribution.put("delivered", deliveredOrders);
                orderStatusDistribution.put("cancelled", cancelledOrders);
                analytics.put("orderStatusDistribution", orderStatusDistribution);

                // 每日订单趋势
                List<Map<String, Object>> dailyOrders = new ArrayList<>();
                for (int i = days - 1; i >= 0; i--) {
                    Map<String, Object> dayOrder = new HashMap<>();
                    dayOrder.put("date", mockDataGenerator.generateDateTime(i).substring(0, 10));
                    dayOrder.put("orders", mockDataGenerator.generateQuantity(5, 50));
                    dayOrder.put("revenue", mockDataGenerator.generatePrice(200, 2000).doubleValue());
                    dailyOrders.add(dayOrder);
                }
                analytics.put("dailyOrders", dailyOrders);
            } else {
                // TODO: 实现订单分析逻辑
                // 1. 统计订单数量、状态分布
                // 2. 分析订单趋势、退货率等

                analytics.put("totalOrders", 0);
                analytics.put("pendingOrders", 0);
                analytics.put("shippedOrders", 0);
                analytics.put("cancelledOrders", 0);
                analytics.put("returnRate", "0%");
            }

        } catch (Exception e) {
            log.error("获取订单分析失败: storeId={}", storeId, e);
        }

        return analytics;
    }

    /**
     * 获取低库存商品
     */
    private List<Map<String, Object>> getLowStockItems(Long storeId) {
        List<Map<String, Object>> items = new ArrayList<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据生成低库存商品
                int count = mockDataGenerator.generateQuantity(5, 20);
                for (int i = 0; i < count; i++) {
                    Map<String, Object> item = new HashMap<>();
                    item.put("asin", mockDataGenerator.generateAsin());
                    item.put("sku", mockDataGenerator.generateSku());
                    item.put("title", mockDataGenerator.generateProductName());
                    item.put("currentStock", mockDataGenerator.generateQuantity(1, 10)); // 低库存
                    item.put("threshold", mockDataGenerator.generateQuantity(15, 30)); // 阈值
                    item.put("category", mockDataGenerator.generateCategory());
                    item.put("lastUpdated", mockDataGenerator.generateDateTime(3));
                    items.add(item);
                }
            } else {
                // TODO: 实现低库存商品查询逻辑
                // 1. 查询库存低于阈值的商品
                // 2. 返回商品信息和库存数量
            }

        } catch (Exception e) {
            log.error("获取低库存商品失败: storeId={}", storeId, e);
        }

        return items;
    }

    /**
     * 获取缺货商品
     */
    private List<Map<String, Object>> getOutOfStockItems(Long storeId) {
        List<Map<String, Object>> items = new ArrayList<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据生成缺货商品
                int count = mockDataGenerator.generateQuantity(2, 15);
                for (int i = 0; i < count; i++) {
                    Map<String, Object> item = new HashMap<>();
                    item.put("asin", mockDataGenerator.generateAsin());
                    item.put("sku", mockDataGenerator.generateSku());
                    item.put("title", mockDataGenerator.generateProductName());
                    item.put("currentStock", 0); // 缺货
                    item.put("category", mockDataGenerator.generateCategory());
                    item.put("outOfStockSince", mockDataGenerator.generateDateTime(10));
                    item.put("lastSaleDate", mockDataGenerator.generateDateTime(15));
                    item.put("averageDailySales", mockDataGenerator.generateQuantity(1, 10));
                    items.add(item);
                }
            } else {
                // TODO: 实现缺货商品查询逻辑
                // 1. 查询库存为0的商品
                // 2. 返回商品信息和缺货时间
            }

        } catch (Exception e) {
            log.error("获取缺货商品失败: storeId={}", storeId, e);
        }

        return items;
    }

    /**
     * 获取滞销商品
     */
    private List<Map<String, Object>> getSlowMovingItems(Long storeId) {
        List<Map<String, Object>> items = new ArrayList<>();

        try {
            if (mockEnabled) {
                // 使用模拟数据生成滞销商品
                int count = mockDataGenerator.generateQuantity(3, 12);
                for (int i = 0; i < count; i++) {
                    Map<String, Object> item = new HashMap<>();
                    item.put("asin", mockDataGenerator.generateAsin());
                    item.put("sku", mockDataGenerator.generateSku());
                    item.put("title", mockDataGenerator.generateProductName());
                    item.put("currentStock", mockDataGenerator.generateQuantity(10, 100));
                    item.put("category", mockDataGenerator.generateCategory());
                    item.put("lastSaleDate", mockDataGenerator.generateDateTime(60)); // 60天前
                    item.put("slowMovingDays", mockDataGenerator.generateQuantity(30, 90));
                    item.put("totalValue", mockDataGenerator.generatePrice(100, 1000).doubleValue());
                    item.put("recommendedAction", mockDataGenerator.randomChoice(new String[]{"降价促销", "广告推广", "清仓处理"}));
                    items.add(item);
                }
            } else {
                // TODO: 实现滞销商品查询逻辑
                // 1. 查询长期无销售的商品
                // 2. 返回商品信息和滞销天数
            }

        } catch (Exception e) {
            log.error("获取滞销商品失败: storeId={}", storeId, e);
        }

        return items;
    }

    /**
     * 计算预警级别
     */
    private String calculateAlertLevel(int lowStockCount, int outOfStockCount) {
        if (outOfStockCount > 10 || lowStockCount > 50) {
            return "HIGH";
        } else if (outOfStockCount > 5 || lowStockCount > 20) {
            return "MEDIUM";
        } else if (outOfStockCount > 0 || lowStockCount > 0) {
            return "LOW";
        } else {
            return "NORMAL";
        }
    }

}
